Title: Research report – AI-powered VR learning
Exploration of Ethical Leadership: Reimagining the future of learning spaces in RMIT’s MBA and EMBA program with AI-powered VR for data analysis, adaptive learning and accelerated skill development.
Vincent Vu
Design Think for Business (Executive)
Executive Master of Business Administration
Traditional learning spaces often limit students’ ability to engage with complex problems in a realistic setting. With a trend in innovation towards AI, for students studying RMIT’s Master of Business Administration (MBA) and Executive Master of Business Administration (EMBA) program, AI-driven Virtual Reality (VR) offers the potential for immersive learning environments that provide real-time performance tracking and adaptive learning aligning with RMIT’s emphasis on active, authentic and applied learning experiences. (RMIT University, 2023)
This research explores how AI-driven VR can create immersive learning experiences, evaluate student performance and create personalised learning trajectories within RMIT’s MBA program. It adopts a design thinking perspective, focusing on the “engage” and “evaluate” stages.
Virtual Reality (VR) and Artificial Intelligence (AI) have demonstrated unprecedented potential in enhancing the future learning space, offering immersive learning experiences and personalised feedback technology. Research shows a general potential of VR and AI in education (Rong, Lian and Tang, 2022; Sharrab et al., 2023; Gandedkar, Wong and Darendeliler, 2021; Luckin and Cukurova, 2019), existing studies offer limited guidance on their application within the specific context of the MBA and EMBA program. However, more research is needed to explore how AI-driven VR simulation and feedback systems can target developing essential business skills like critical negotiation, strategic decision-making and leadership. The study aims to address this gap.
VR and AI offer a powerful synergy for revolutionising education. VR excels in creating immersive environments that transcend the limitations of traditional classrooms, allowing students to actively engage with complex simulated scenarios (Makransky, Terkildsen and Mayer, 2019). VR and AI promote active learning, a “learning-by-doing” approach that can accelerate skill development (Gandedkar, Wong and Darendeliler, 2021). AI introduces data-driven personalisation, providing tailored feedback and adapting learning experiences to individual needs (Hwang and Chang, 2021). VR’s immersive experience and AI’s user-based personalisation have the potential to deepen learning objectives and foster opportunities for student success (Luckin and Cukurova, 2019).
The MBA program requires learning experiences that extend beyond the traditional classroom. MBA and EMBA graduates are expected to be proficient in complex skills such as negotiation, strategic decision-making and leadership (Pepperdine University, 2018), often developed through real-world practice. Tang and Huang (2019) indicate the potential of VR-enhanced education for MBA and EMBA students by offering new ways to address limitations associated with traditional teaching methods. Research by Oyelere et al. (2020) and Hamilton et al. (2021) demonstrates VR’s potential to deliver immersive, personalised learning experiences with evidence of improved learning outcomes compared to traditional methods. AI-driven VR has the potential to offer immersive learning environments that align with RMIT’s emphasis on active, authentic and applied learning, offering a bridge between theory and practice.
VR environments can be integrated to collect real-time data on interactions, actions and behaviours within the simulated space. The data and information collected within the simulated space often exceed traditional assessments, providing rich insights into decision-making processes, problem-solving approaches and skill application under pressure (Radianti et al., 2020; Merchant et al., 2014). AI algorithms can process complex data in real-time, offering nuanced evaluations and identifying specific strengths and areas of improvement.
Analysing VR performance data with AI enables the creation of highly personalised learning pathways for MBA and EMBA students (Mohammed, 2023). Adaptive learning systems can adjust the difficulty of subsequent simulations, focus on targeted skill development and offer customised learning recommendations (Motejlek and Alpay, 2021; Mohammed, 2023). This approach ensures students are progressively challenged at the right skill level, with simulations adapting to address their specific needs or areas requiring additional attention.
AI-driven feedback systems integrated into VR experiences can provide timely, relevant and actionable guidance (Motejlek and Alpay, 2021; Mohammed, 2023). Natural Language Processing (NLP) techniques can analyse student interactions within the simulation and provide real-time context-specific feedback (Lester, Mott and Robison, 2022). Through generative AI, AI can generate feedback reports highlighting student performance patterns using data collected during the simulation to support self-reflection and instructor analysis for focused interventions and recommendations.
Integrating AI-driven VR in RMIT’s MBA/EMBA program has proven potential but raises ethical concerns. Ethical considerations revolve around data protection, privacy of sensitive student performance, potential biases within AI algorithms, equity and accessibility (Zhuk, 2024)
A mixed-methods study investigated current MBA/EMBA students’ perspectives on AI-driven VR. The research sample included MBA and EMBA students from diverse career backgrounds to identify trends and differences in management styles and career pathways.
Current MBA and EMBA students were selected to identify and explore the gaps within our research topic. This research involved semi-structured interviews incorporating a questionnaire to capture qualitative insights and quantitative information on technology attitudes and learning preferences.
Background: Current MBA/EMBA students from diverse career backgrounds.
Gender: Male, female and undefined groups.
Age: Evenly dispersed age group.
Data Collection: Semi-structured interview and structured questionnaire.
| Participant 1 | Participant 2 | 30-35 | Participant 4 | Participant 5 | |
|---|---|---|---|---|---|
| Age | 26-30 | 30-35 | Female | 36-40 | 20-25 |
| Gender | Female | Male | Bachelor’s Degree (Commerce) | Master’s Degree (Public Health) | Male |
| Previous Education | Bachelor’s Degree (Economics) | Master’s Degree (Engineer) | Classroom | Internship | Bachelor’s Degree (Computer Science) |
| Learning Style | Internship | Classroom | Neutral | Somewhat Uncomfortable | Online |
| Technology Comfort | Very Comfortable | Somewhat Comfortable | No | No | Very Comfortable |
| VR Ownership | No | Yes (Gaming Headset) | Somewhat Uninterested | Neutral | Yes (High-End VR Setup) |
| AI-driven VR Interest | Very Interested | Somewhat Interested | Very Interested |
The following analysis highlights key themes and trends that emerged from this research.
Key themes
Immersive learning: Participants pursuing technology-based leadership embrace AI-driven VR’s immersive potential, while those inclined towards more traditional roles appreciate its focus on practical skill development. Students have indicated that current studies are too ‘theoretical’ and ‘abstract’, wanting ‘more focus on doing than just learning the theories.’ Students strongly desire immersive learning to be able to see what they’re being taught.
Theory and practical: Participants from all backgrounds express a common theme of bridging the gap between theory and real-world application. Responses include a want to ‘try applying some of these concepts’ or how it can ‘connect the dots’ between study and work. Current learning structures struggle to effectively enable students to apply theoretical knowledge to practical learning. Students look to connect the dots between traditional classrooms and real-world experiences.
Human-guided AI/VR: While open to AI and VR’s potential for skill development, participants expressed concerns about AI and VR replacing human interactions. Participants indicated they would want their feedback backed by ‘experienced mentors,’ with trust and transparency, questioning whether the AI’s feedback is ‘reliable’. Participants have concerns about whether the data used to train AI is trustworthy or from a reputable source. Students express that while AI/VR has potential, professional guidance is required to ensure the AI feedback is correct and just.
Personalisation: Participants express a requirement for personalised AI-driven VR experiences customised to the specific skills and real-world scenarios relevant to their career pathway. This means that the AI/VR learning experience should be relevant to them, including their current skill level and desired goals.
Accessibility and equality: While tech comfort was generally high, only two participants owned VR equipment. This indicates a potential barrier and highlights the need to address accessibility.
Trust and transparency: Participants require clarity on how AI can replicate the dynamics of a real-world environment. Data privacy was a common theme among participants. Participants indicate concerns about what or who the AI is being ‘trained on’, whether their data is collected and being ‘used for non-educational purposes’, and a general concern for ‘data protection’.
These findings suggest that MBA/EMBA participants see the potential of AI-driven VR enhancing their learning experience. From our user group, participants indicated a requirement for transparency around AI-generated feedback and trained datasets. While tech-savvy participants embrace data-driven insights, others prefer AI feedback coupled with mentors. Primary and secondary research reflects similar concerns on how VR can be implemented to tailor simulations that mirror real-world situations for different fields. Participants also expressed concerns about the balance between technology and human connection.
The ‘how might we’ statement is typically the problem statement that the proposed research aims to address.
Through this research on traditional MBA problem learning structure. Traditional MBA program learning structures often struggle to provide the immersive, practice-oriented experiences essential for skill development. As a result, the revised how might we statement:
How might we leverage AI-driven VR with real-time feedback to create immersive, personalised and practice-oriented environments that can enhance skill development, student engagement and learning outcomes within RMIT’s MBA program while considering costs, accessibility and ethical concerns?
This research explored how AI-driven VR could enhance the learning experience within RMIT’s MBA program. The literature review highlighted the potential of VR and AI in education while demonstrating a knowledge gap concerning their applications for skill development. Primary research involving current RMIT MBA students revealed a strong interest in the potential of AI-driven VR for personalised skill development. Themes include the desire for immersive, practice-oriented learning that bridges the gap between theory and real-world scenarios. Students also emphasised the importance of ethical considerations like data privacy and accessibility and the need for more precise guidance between human interaction and AI-driven systems.
These findings indicate the potential that AI-driven VR could bring to the MBA program while highlighting critical areas for further investigation. Questions remain about how VR simulations can effectively simulate the dynamic environment of a real-world situation, the balance between AI guidance and human mentorship, ethical concerns for responsible implantation and costs. Future research focused on these open questions will be crucial in determining the best ways to explore the full potential of AI-driven VR for enhancing the future classroom and MBA learning experience.
Chu, S.-T., Hwang, G.-J., & Tu, Y.-F. (2022). 'Artificial intelligence-based robots in education: A systematic review of selected SSCI publications'. Computers and Education: Artificial Intelligence, 3, 100091. https://doi.org/10.1016/j.caeai.2022.100091
Gandedkar, N.H., Wong, M.T. and Darendeliler, M.A. (2021), 'Role of virtual reality (VR), augmented reality (AR) and artificial intelligence (AI) in tertiary education and research of orthodontics: An insight', Seminars in Orthodontics, 27(2), 69-77. ISSN 1073-8746. https://doi.org/10.1053/j.sodo.2021.05.003
Hamilton, D., McKechnie, J., Edgerton, E. and Wilson, C. (2021). 'Immersive virtual reality as a pedagogical tool in education: a systematic literature review of quantitative learning outcomes and experimental design'. Journal of Computers in Education, 8(1), 1-32. https://doi.org/10.1007/s40692-020-00169-2
Hwang, G.-J. and Chang, C.-Y. (2023) 'A review of opportunities and challenges of chatbots in education', Interactive Learning Environments, 31(7), 4099–4112. https://doi.org/10.1080/10494820.2021.1952615
Luckin, R., Cukurova, M. (2019), 'Designing educational technologies in the age of AI: A learning sciences‐driven approach', British Journal of Educational Technology, 50(6), 2824-2838. https://doi.org/10.1111/bjet.12861
Makransky, G., Terkildsen, T. S. and Mayer, R. E. (2019). 'Adding immersive virtual reality to a science lab simulation causes more presence but less learning'. Learning and Instruction, 60, 225-236. https://doi.org/10.1016/j.learninstruc.2017.12.007
Merchant, Z., Goetz, E. T., Cifuentes, L., Keeney-Kennicutt, W., & Davis, T. J. (2014). 'Effectiveness of virtual reality-based instruction on students’ learning outcomes in K-12 and higher education: A meta-analysis'. Computers & Education, 70, 29-40. https://doi.org/10.1016/j.compedu.2013.07.033
Mohammed, R. (2023). 'Investigating AI-Powered Tutoring Systems that Adapt to Individual Student Needs, Providing Personalized Guidance and Assessments'. The Eurasia Proceedings of Educational and Social Sciences. 31. 67-73. https://doi.org/10.55549/epess.1381518
Motejlek, J. and Alpay, E. (2021). 'Taxonomy of Virtual and Augmented Reality Applications in Education'. IEEE Transactions on Learning Technologies, 14(3), 415-429. https://doi.org/10.1109/TLT.2021.3092964
Oyelere, S.S., Bouali, N., Kaliisa, R., Obaido, G., Yunusa, A.A. and Jimoh, E.R. (2020). ‘Exploring the trends of educational virtual reality games: a systematic review of empirical studies’. Smart Learning Environments, 7, 1-22. https://doi.org/10.1186/s40561-020-00142-7
Pepperdine University. (2018). 'The importance of soft skills development'. https://bschool.pepperdine.edu/blog/posts/soft-skills-business.htm (Accessed: 25 March 2024).
Radianti, J., Majchrzak, T. A., Fromm, J. & Wohlgenannt, I. (2020). 'A systematic review of immersive virtual reality applications for higher education: Design elements, lessons learned, and research agenda'. Computers & Education, 147, 103778. https://doi.org/10.1016/j.compedu.2019.103778
RMIT University (2023). 'RMIT’s Education Plan to 2025: Learning through Life and Work'. https://www.rmit.edu.au/students/my-course/enrolment/enrol-new-student. (Accessed: 25 March 2024).
Rong, Q., Lian, Q. and Tang, T. (2022). 'Research on the Influence of AI and VR Technology for Students' Concentration and Creativity'. Frontiers in Psychology, 13, 767689. https://doi.org/10.3389/fpsyg.2022.767689
Sharrab, Y., Almutiri, N.T., Tarawneh, M., Alzyoud, F., Al-Ghuwairi, A.R. and Al-Fraihat, D. (2023). 'Toward Smart and Immersive Classroom based on AI, VR, and 6G'. International Journal of Emerging Technologies in Learning, 18(2), 4-16. https://doi.org/10.3991/ijet.v18i02.35997
Tang, X. and Huang, J. (2019). 'Research on MBA Educational Practice Innovation Based on VR in 2019 3rd International Conference on Data Science and Business Analytics (ICDSBA)'. Istanbul, Turkey, 20-23 November 2019, IEEE, 33-38. https://doi.org/10.1109/ICDSBA48748.2019.00018
Zhuk, A. (2024). 'Ethical implications of AI in the Metaverse'. AI Ethics, https://doi.org/10.1007/s43681-024-00450-5
Technology and VR
How comfortable are you using technology?
▢ Very comfortable
▢ Somewhat comfortable
▢ Neutral
▢ Somewhat uncomfortable
▢ Very uncomfortable
Do you currently own any Virtual Reality (VR) equipment?
▢ Yes
▢ No
If so, how frequently do you use your VR equipment?
▢ Very frequent
▢ Frequent
▢ Neutral
▢ Rarely
▢ Never
Attitudes towards AI-driven VR
How interested are you in the potential of AI-driven VR for learning and development?
▢ Very interested
▢ Somewhat interested
▢ Neutral
▢ Somewhat uninterested
▢ Very uninterested
What are your thoughts on the potential of AI-driven VR for developing critical business skills (e.g., negotiation and decision-making) in an MBA program?
▢ Very valuable
▢ Somewhat valuable
▢ Neutral
▢ Somewhat not valuable
▢ Not valuable at all
Experience with MBA programs
What aspects of the MBA teaching environment have been particularly effective or less effective for you?
What are the biggest strengths and weaknesses you’ve observed in the MBA teaching environment?
How important is developing practical skills (e.g., negotiation, decision-making) in your MBA program experience?
What is your reasoning for studying for an MBA or EMBA program?
What are your career goals after completing your MBA/EMBA?
Attitudes towards VR learning
What potential benefits or drawbacks do you see in using VR for an immersive learning experience in your MBA program?
AI-driven feedback
Do you find personalised and real-time feedback valuable during your learning process, and if so, why?
How comfortable would you be receiving performance feedback from AI in a VR simulation environment?
Learning preferences
How does a traditional classroom foster active participation and engagement in your learning process?
How do you think VR simulations could enhance your learning experience and engagement?
Ethical considerations
What, if any, ethical concerns do you see with using AI-driven VR for learning in an MBA program?
How important is ensuring data privacy and security when using VR simulations for educational purposes?
Interest and adoption
Would you be interested in participating if offered an AI-driven VR learning experience within your MBA program? Why or why not?
What additional information or assurances would be needed for you to feel comfortable integrating AI-driven VR into your MBA learning journey?
Demographics
Age:
▢ 20-25
▢ 26-30
▢ 31-35
▢ 35-40
▢ 41-45
▢ 45-50
Gender:
▢ Male
▢ Female
▢ Non-binary
▢ Prefer not to answer
Highest level of education completed:
▢ Bachelor’s Degree
▢ Master’s Degree
▢ Doctoral Degree
▢ Other (please specify)
Career focus:
(Economics, Technology, Engineering, Marketing, Communication, Health, etc)
What is your preferred learning style:
▢ Lectures
▢ Classroom
▢ Online
▢ Readings
▢ Internship
Participant 1
Summary
Participant 2
Summary
Participant 3
Summary
Participant 4
Summary
Participant 5
Summary
This journal article and research report was updated on 13 May 2025.
Changes made:
